Using Satellite Data on Nighttime Lights Intensity to Estimate Contemporary Human Migration Distances
(2017) In Annals of the Association of American Geographers 107(3). p.591-605- Abstract
- For well over a century, migration researchers have recognized the lack of adequate distance measures to be a key obstacle for advancing understanding of internal migration. The problem arises from the convention of spatially defining migration as the crossing of administrative borders. Because administrative regions vary in size, shape, and settlement patterns, it is difficult to tell how far movers go, raising doubts about the generalizability of research in the field. This article shows that satellite data on nighttime lights can be used to infer accurate measures of migration distance. We first use the intensity of nighttime lights to locate mean population centers that closely correspond to mean population centers calculated from... (More)
- For well over a century, migration researchers have recognized the lack of adequate distance measures to be a key obstacle for advancing understanding of internal migration. The problem arises from the convention of spatially defining migration as the crossing of administrative borders. Because administrative regions vary in size, shape, and settlement patterns, it is difficult to tell how far movers go, raising doubts about the generalizability of research in the field. This article shows that satellite data on nighttime lights can be used to infer accurate measures of migration distance. We first use the intensity of nighttime lights to locate mean population centers that closely correspond to mean population centers calculated from actual population data. Until now, locating mean population centers accurately has been problematic, as it has required highly disaggregated population data, which are lacking in many countries. The nighttime lights data, which are freely available on a yearly basis, solve this challenge. We then show that this information can be used to accurately estimate migration distances. (Less)
- Abstract (Swedish)
- For well over a century, migration researchers have recognized the lack of adequate distance measures to be a key obstacle for advancing understanding of internal migration. The problem arises from the convention of spatially defining migration as the crossing of administrative borders. Since administrative regions vary in size, shape, and settlement patterns, it is difficult to tell how far movers go, raising doubts about the generalizability of research in the field. This article shows that satellite data on nighttime lights can be used to infer accurate measures of migration distance. We first use the intensity of nighttime lights to locate mean population centers that closely correspond to mean population centers calculated from actual... (More)
- For well over a century, migration researchers have recognized the lack of adequate distance measures to be a key obstacle for advancing understanding of internal migration. The problem arises from the convention of spatially defining migration as the crossing of administrative borders. Since administrative regions vary in size, shape, and settlement patterns, it is difficult to tell how far movers go, raising doubts about the generalizability of research in the field. This article shows that satellite data on nighttime lights can be used to infer accurate measures of migration distance. We first use the intensity of nighttime lights to locate mean population centers that closely correspond to mean population centers calculated from actual population data. Until now, locating mean population centers accurately has been problematic as it has required highly disaggregated population data, which are lacking in many countries. The nighttime lights data, which are freely available on a yearly basis, solves this challenge. We then show that this information can be used to accurately estimate migration distances. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/657804ca-8785-48d9-a8d7-8bd48e24f174
- author
- Niedomysl, Thomas LU ; Hall, Ola LU ; Archila, Maria LU and Ernstson, Ulf
- organization
- publishing date
- 2017-05-04
- type
- Contribution to journal
- publication status
- published
- subject
- in
- Annals of the Association of American Geographers
- volume
- 107
- issue
- 3
- pages
- 591 - 605
- publisher
- Taylor & Francis
- external identifiers
-
- scopus:85014545640
- ISSN
- 0004-5608
- DOI
- 10.1080/24694452.2016.1270191
- language
- English
- LU publication?
- yes
- id
- 657804ca-8785-48d9-a8d7-8bd48e24f174
- date added to LUP
- 2016-10-10 09:34:50
- date last changed
- 2024-01-04 13:58:47
@article{657804ca-8785-48d9-a8d7-8bd48e24f174,
abstract = {{For well over a century, migration researchers have recognized the lack of adequate distance measures to be a key obstacle for advancing understanding of internal migration. The problem arises from the convention of spatially defining migration as the crossing of administrative borders. Because administrative regions vary in size, shape, and settlement patterns, it is difficult to tell how far movers go, raising doubts about the generalizability of research in the field. This article shows that satellite data on nighttime lights can be used to infer accurate measures of migration distance. We first use the intensity of nighttime lights to locate mean population centers that closely correspond to mean population centers calculated from actual population data. Until now, locating mean population centers accurately has been problematic, as it has required highly disaggregated population data, which are lacking in many countries. The nighttime lights data, which are freely available on a yearly basis, solve this challenge. We then show that this information can be used to accurately estimate migration distances.}},
author = {{Niedomysl, Thomas and Hall, Ola and Archila, Maria and Ernstson, Ulf}},
issn = {{0004-5608}},
language = {{eng}},
month = {{05}},
number = {{3}},
pages = {{591--605}},
publisher = {{Taylor & Francis}},
series = {{Annals of the Association of American Geographers}},
title = {{Using Satellite Data on Nighttime Lights Intensity to Estimate Contemporary Human Migration Distances}},
url = {{http://dx.doi.org/10.1080/24694452.2016.1270191}},
doi = {{10.1080/24694452.2016.1270191}},
volume = {{107}},
year = {{2017}},
}